AN ANALYSIS OF MACROECONOMIC DETERMINANTS … 4(1), 41-57.pdf · AN ANALYSIS OF MACROECONOMIC...

Asian Economic and Financial Review, 2014, 4(1):41-57

41

AN ANALYSIS OF MACROECONOMIC DETERMINANTS OF COMMERCIAL

BANKS PROFITABILITY IN MALAYSIA FOR THE PERIOD 1995-2011

Mirza Vejzagic

Finance lecturer, Limkokwing University of Creative Technology Malaysia and Ph.D. candidate,

International Centre for Education in Islamic Finance, Malaysia

Hashem Zarafat

Finance lecturer, Limkokwing University of Creative Technology Malaysia and holds Master of Business

Administration with concentration in Finance, Multimedia University, Malaysia

ABSTRACT

This paper investigates the macroeconomics factors that stimulate banks’ profitability. A standard

regression model is used to identify macroeconomics determinants that significantly contribute to

profitability, expressed through return on assets (ROA), of commercial banks in Malaysia. The

determinant factors under consideration are real gross domestic product growth, inflation

(expressed through consumer price index), and real interest rates. The paper incorporates seven

banks, namely, CIMB, Public Bank, Maybank, Affin Bank, RHB Bank, Alliance Bank and Hong

Leong Bank for the period 1995 to 2011. In order to present research in most accurate way, the

paper looked into the relationship between profitability of all banks (expressed through mean of

ROAs), as well as every single individual bank, with mentioned macroeconomic determinants.

Model demonstrated overall significance for mean of all banks, and three individual banks,

namely, Maybank, Public Bank and Hong Leong Bank. Findings show that for mean of all banks,

as well as Maybank, Public Bank and Hong Leong Bank, real GDP is significant and have positive

relationship with confidence level of 1% and 5%. This paper illustrated that in Malaysian case,

inflation (CPI) is not significant for mean of all banks and Maybank. On the contrary, for Public

Bank and Hong Leong Bank inflation (CPI) is significant, with negative relationship. Lastly, the

outcomes of this paper exemplified that in Malaysia real interest rate has no relation with banks’

profitability. From the empirical estimation, it is suggested that for the banks’ profitability the

growth of gross domestic product must be in place in order to stimulate lending and borrowing

activities. In addition, it is proposed that for the banking sector in order to preserve on

profitability, the anticipation of inflation must be in place to shelter revenue and reduce cost of the

banks.

Keywords: Banking, Profitability (ROA), Gross Domestic Product, Inflation Rate, Interest Rate

Asian Economic and Financial Review

journal homepage: http://aessweb.com/journal-detail.php?id=5002


42

1. INTRODUCTION

Profit is the foremost motive for everyone to put an immense effort and make the business

successful, since profit is a central source of (re) investment funds. When it comes to banking

sector, the importance of banks’ profitability can be appraised at the micro and macro levels of the

economy (see for instance, (Bourke, 1989; Chaudhry et al., 1995; Kosmidou et al., 2007;

Kosmidou, 2008). Accordingly, numerous studies have investigated determinants of bank

profitability and banks performance in domestic and foreign markets in various countries around

the world (Saunders and Schumacher, 2000; Williams, 2003; Staikouras and Geoffrey, 2004;

Chantapong, 2005; Kosmidou et al., 2007; Kosmidou et al., 2008; Kosmidou and Zopounidis,

2008). In Malaysia, the banking sector had experienced immense and impressive structural changes

in order to remain more competitive in the Asian financial industry and to be more resilient to

various external shocks. In recent times, research has focused on the impact of external

macroeconomic factors on bank performance and profitability determinants (e.g., (Guru et al.,

1999; Rasiah, 2010; Mohd and Tumin, 2011). Bank profitability is expected to be receptive to

macroeconomic control variables. At the macro level, a sound and profitable banking sector is

better able to withstand negative shocks and contribute to the stability of the financial system

(Saunders and Schumacher, 2000; Yu and Gan, 2010).

This paper attempts to investigate the impact of macroeconomic determinants on banks’

profitability in Malaysia. In other word, this study aims to explore the nature of relationship

between the profitability of banks in Malaysia expressed through Return on Assets (ROA) and the

three major macroeconomic variables, i.e. Real GDP growth rate, Inflation which is expressed

through Consumer Price Index, and Real Interest Rates. The paper incorporates seven banks,

namely, CIMB, Public Bank, Maybank, Affin Bank, RHB Bank, Alliance Bank and Hong Leong

Bank during the period 1995 to 2011. In order to present research in most accurate way, the paper

will look into the relationship between profitability of all banks (expressed through mean of ROAs

for these seven banks), as well as three single individual banks, with mentioned macroeconomic

determinants.

2. OBJECTIVES OF RESEARCH

The objective of this paper is to clearly identify significant macroeconomic determinants of

commercial banks profitability in Malaysia for the period 1995-2011. Furthermore, it will examine

how the macroeconomic factors contribute to the variation in commercial bank profitability over

specific time in Malaysia. Lastly, this study will try to show which particular banks’ profitability is

mostly affected by the variations in macroeconomic factors that are not under the control of bank

management.

3. LITERATURE REVIEW

Extensive literatures have previously investigated the link between bank profitability which is

commonly expressed by either Return on Assets (ROA) or Return on Equity (ROE) and

macroeconomics variables which generally comprise real GDP growth, inflation (i.e., price level


43

changes), and interest rates (Demirgüç-Kunt and Huizinga, 1999; Aburime, 2008; Athanasoglou et

al., 2008; Sufian and Chong, 2008; Alexiou and Sofoklis, 2009; Sufian, 2009; Sufian and

Habibullah, 2009; Sufian and Habibullah, 2010; Ramadan et al., 2011). These studies are

frequently carried by monetary authorities and they are usually observing to what extend and how

important are influence of external determinants on banks’ performance and profitability.

Examination of potential macroeconomics determinants as factors of bank profitability generally

involves the application of different types of regression analysis, time series analysis, composite

character and range of data applied by researcher (see, for instance, (Goddard et al., 2004; Sufian

and Habibullah, 2009; Sufian and Habibullah, 2010).

One of the earliest studies that examined relationship between bank profitability and

macroeconomic variables were conducted by Molyneux and Thornton (1992). They looked into

economic growth as “primary” indicator of bank profitability, while taking into account the

importance of interest rates and inflation. Economic growth should increase bank profits through

enhanced demand for household and business loans. These loans generate good returns to

commercial banks, ensuing higher profits. An additional similarly significant reason why profits

increase with economic growth is that smaller numbers of loans defaults occur during stage of

strong growth (Molyneux and Thornton, 1992). In addition, they elaborated that interest rate

movements are assumed to correlate with banks’ profits. In most cases, banks rely profoundly on

short-term deposits as a source of funds. The interest paid on the deposits varies in accordance with

the interest rates set by the European Central Bank (ECB), which in turn are closely linked to

inflationary expectations. The findings of their study also indicate that there is a significant,

positive relationship between interest rates and bank’s profitability. While Molyneux and Thornton

(1992) study was mainly elaborating impact of economic growth and interest rates on bank

profitability, empirical evidence from cross-country studies by Demirgüç-Kunt and Huizinga

(1999) suggest that inflation improves bank profitability. They confer that the positive relationship

between inflation and the bank profitability implies that bank income during inflation increases

more than bank costs. High inflation rates are also commonly related to high loan interest rates, and

consequently, high incomes. Banks also attain higher earnings from floats or delays in crediting

customer accounts in an inflationary environment. However, if inflation is unanticipated and banks

are sluggish in adjusting their interest rates, then there is a possibility that bank costs may increase

faster than bank revenues and hence adversely affect bank profitability (Demirgüç-Kunt and

Huizinga, 1999; Tan and Floros, 2012).

Even though majority of prior studies carried on correlation between bank profitability and

macroeconomic determinants have propensity to be positively related, the study carried by Naceur

(2003) indicated otherwise. He investigated the effect of bank’s characteristics, financial structure

and macroeconomic indicators on bank’s net interest margins and profitability in the Tunisian

banking industry for the 1980-2000 period. The measurements of bank’s profitability were ROA

and ROE as dependent variables. The study used inflation and GDP per capita growth as

macroeconomic measures which represented explanatory variables. What was exceptionally

interesting in his findings is that the macroeconomic indicators i.e. inflation and growth were


44

insignificant in both spread and profit regressions. According to him, this may suggest that banks

tend to not profit in inflationary environment. In addition, growth does not reflect any aspects of

banking regulations, while technology advances in the banking sector were omitted from the

regressions. Pasiouras and Kosmidou (2007) conducted a research to study and to compare the

performance of domestic and foreign banks operating in the 15 European Union countries over the

period 1995–2001. They used return on average assets (ROAA) to evaluate bank’s performance

and bank’s total assets, the cost to income ratio, the ratio of equity to assets and the ratio of bank’s

loans divided by customers and short term funding as the internal factors. For the external factors,

they used gross domestic product growth and inflation to evaluate the macroeconomic conditions.

According to their findings, GDP growth is a measure of economic activity of a country. Higher

economic growth encourages banks not only to lend more and permits them to charge higher

margins, but also to improve the quality of their assets. They found a positive relationship between

real GDP and the bank profitability, as well as between inflation and bank profitability Pasiouras

and Kosmidou (2007). In a nutshell, an evaluation of previous research on the correlation between

bank profitability and macroeconomics variables normally provide support to the theoretical

framework which advocates a high relationship between them, and therefore making

macroeconomic variables important for determining bank profitability. However, taking into

account latest findings of the impacts related to anticipation of inflation, as well as suggestions that

interest rate spread or margin should be used as explanatory variable in place of just market interest

rates (Guru et al., 1999), it is of the essence that forthcoming research have to address several

others related issues such as expectation of price differential on the global level, interest rate

spread, the role of central bank in exchange rate and money supply as well as to take in

consideration latest economics and financial crises.

4. EMPIRICAL APPROACH AND DATA

4.1. Specification of Empirical Model

Research has previously used linear regression and correlation analysis by Ordinary Least

Squares (OLS) to pinpoint the relationship between bank profitability (ROA) and independent

variables namely, real GDP growth (RGDP), inflation, i.e. consumer price index (CPI), and real

interest rate (RINT). In a linear regression setting, dependent variable Y (endogenous) is denoted as

ROA, while the independent variables X1, X2 and X3 are denoted as RGDP, CPI and RINT.

ROAt= α + β1RGDPt + β2CPIt + β3RINTt + εt

where α represents intercept, β represents slope coefficient, while ε represents error term.

4.2. Expected Relation

Real gross domestic product (GDP) growth is among the most commonly used macroeconomic

indicators, as it is a measure of total economic activity within an economy. The real GDP growth

used in this study is expected to have a positive impact on bank profitability in the line with the

literature (e.g., (Pasiouras and Kosmidou, 2007). Inflation, expressed here through consumer price

index (CPI), is another important macroeconomic indicator. Even though there were studies


45

supporting the significant positive or negative relationship between inflation and bank profitability

(e.g., (Demirgüç-Kunt and Huizinga, 1999), Naceur (2003) research showed that inflation is

insignificant for bank profitability. Therefore, in this study, relation is expected to be uncertain and

dependable on the analyzed results. As for the interest rate, according to previous studies, the

relation between the interest rate and bank profits is expected to be positive. Molyneux and

Thornton (1992), for example, indicated that bank profits increases as interest rate rises.

Accordingly, Demirgüç-Kunt and Huizinga (1999) demonstrated the link between real interest rates

and profitability. This study will further explore the relationship between bank profitability and the

real interest rate.

4.3. Estimation Method

The estimation method used for this research is the least square estimation, i.e. the estimation

of β1, β2 and β3 by minimizing the sum of the error square.

4.4. Data Time Period, Number of Observation, Source

This study covers time period between 1995 and 2011. The frequency of data is annual, which

is in total 17 observations. All data used in this study are derived from World Data Bank (World

Development Indicators & Global Development Finance), Bank Negara Malaysia (web site of

Central Bank of Malaysia) and BankScope (world banking information source).

4.5. Definition of Each Variable

Return on Asset (ROA) is a ratio computed by dividing the net income over total assets. ROA

has been used in most banks’ performance studies. ROA measures the profit earned per dollar of

assets and reflect how well bank management use the bank’s real investments resources to generate

profits. Real GDP growth is annual percentage growth rate of GDP at market prices based on

constant local currency. Aggregates are based on constant 2000 U.S. dollars. GDP is the sum of

gross value added by all resident producers in the economy plus any product taxes and minus any

subsidies not included in the value of the products. It is calculated without making deductions for

depreciation of fabricated assets or for depletion and degradation of natural resources.1 Economic

growth (RGDP), which is measured by the real GDP growth rate, is assumed to affect banking

profitability positively. This is because the default risk is lower in upturns than in downturns.

Besides, higher economic growth may lead to a greater demand for both interest and non-interest

activities, thereby improving the profitability of banks.

Inflation as measured by the consumer price index reflects the annual percentage change in the

cost to the average consumer of acquiring a basket of goods and services that may be fixed or

changed at specified intervals, such as yearly. The Laspeyres formula is generally used.2 Inflation is

associated with higher costs as well as higher income. If a bank’s income rises more rapidly than its

1 World Data Bank (World Development Indicators & Global Development Finance)



46

costs, inflation is expected to exert a positive effect on profitability. On the other hand, a negative

coefficient is expected when its costs increase faster than its income. Real interest rate is the

lending interest rate adjusted for inflation as measured by the GDP deflator.3 In the essence of lend-

long and borrow-short argument, banks, in general, may increase lending rates sooner by more

percentage points than their deposit rates. In addition, the rise in real interest rates will increase the

real debt burden on borrowers. This, in turn, may lower asset quality, thereby inducing banks to

charge a higher interest margin in order to compensate for the inherent risk.

5. RESULTS

5.1. Descriptive Statistic

The table above shows that the average ROA for the selected Malaysian commercial banks

during the study period is 0.944 with the minimum of 0.095 and the maximum of almost 1.45. The

standard deviation statistics is 0.331 which indicates that there is variation of the profitability

between the selected banks. When it comes to individual bank profitability the highest mean has

Public Bank, 1.46, while the lowest Affin Bank with 0.529. Maximum is recorded by Public Bank

2.1, while minimum by Affin Bank, -4.16. Standard deviation is highest for Affin Bank, 1.339, and

lowest for Hong Leong Bank, 0.308. Considering independent variables, the mean for real GDP

growth is 5.84%, with max growth reaching 10% and contraction of negative 7.35%. Standard

deviation is 4.32. In other hand, for real interest rate mean is 3.7%, with max of 12.8% and

minimum negative 3.8%. Standard deviation is 4.14. Lastly, inflation mean is 2.618%, with

maximum rise in price recorded 5.44% and minimum 0.583%. Standard deviation is 1.38.



47

5.2. Regression Results4

*Significance at 0.10 level

**Significance at 0.05 level

***Significance at 0.01 level

5.3. Diagnostics Statistics

Given the regression table which showed that overall significance (R-squared) was evident

only for the mean of all banks, as well as three individual banks, namely Maybank, Public Bank

and Hong Leong Bank, study will run the diagnostic test for mentioned significant four models.

*p-value>0.1, therefore Ho cannot be rejected.

4 As presented in regression table above, it can be concluded that model is statistically significant (R-Square) for mean of all

banks at 5% confidence level, as well as for three individual banks, namely, Maybank (1%), Public Bank (1%) and Hong

Leong Bank (5%). However, the model is insignificant for other four banks. Therefore, from here on in, the paper will

consider only banks for which model is significant, i.e. mean of all banks, Maybank, Public Bank and Hong Leong Bank.


48

In testing normality, Jarque-Bera test shows that the error terms for all banks as well as the

three individual banks are normally distributed (For detailed information please refer to appendix

A). For testing Autocorrelation Breusch-Godfrey Serial Correlation LM tests is used. As the

presented table indicates that the probabilities of F statistics for the mean of all banks as well

Public Bank and Hong Leong Bank are above 0.10 with 2 lags, which mean we cannot reject the

null hypothesis and accept that the error terms are not auto correlated. (For detailed information

please refer to appendix B)5.

As can be observed in presented table the White test for Heteroskedasticity for the mean of all

banks is Heteroskadastic, i.e. the P-value of the chi square is 0.0065, what is less than 0.10.

Therefore Ho is rejected6. In contrast, for all individually observed banks the null hypothesis are in

the error term Homoskadastic and cannot be rejected as the P-values of chi-square statistic are

higher than 0.10. (For detailed information please refer to appendix C). For Ramsey’s Mis-

specification test, RESET, the table shows that the P-value for the mean of all banks, as well as

Public Bank and Hong Leong Bank is greater than 0.10, hence the Ho cannot be rejected and we

can conclude that models have been specified correctly. In contrast, for the Maybank the P-Value is

less than 0.10, hence Ho can be rejected, and model has not been specified correctly. (For detailed

information please refer to appendix D). In the case of ARCH test, Chi-square values for the mean

of all banks as well as every individual bank is higher than 0.10, hence we cannot reject the null

hypothesis that states the error variance is not auto corrected. (For detailed information please refer

to appendix E). The charts presented in appendix F, for CUSUM and CUSUMSQ test7, have

provided us the results which shows that there is small break for mean of all banks in the structure

in 2008 but is soon back within the significance level as the alpha and beta have been restored to

normal. Other than the one outlier that shows slight crossing of the 5% significance line we assume

the structure to be stable with 95% confidence.

6. DISCUSSION OF THE RESULTS

As it was mentioned earlier, the results obtained from regression table showed that model as

whole is significant for mean of all banks at 5% confidence level, as well as for three individual

banks, namely, Maybank (1%), Public Bank (1%) and Hong Leong Bank (5%). For other four

banks the model is insignificant. Therefore, the paper will discuss the results only for banks for

which model is significant, i.e. mean of all banks, Maybank, Public Bank and Hong Leong Bank.

5 Table shows that there is autocorrelation in case of Maybank. The remedy for autocorrelation issue is application of

Newey-West methods.

6 The remedy for heteroskedasticity is application of White correction method.

7 For detailed information please refer to appendix F.


49

Overall Performance and Overall Significance

Observation 17

R-squared Adjusted R-squared F-Statistic Prob. of F-statistic

All Banks (Mean) 0.5159** 0.4042 4.6183 0.0207

Maybank 0.8165*** 0.7742 19.2874 0.0000

Public Bank 0.5938 *** 0.5000 6.3353 0.0069

Hong Leong B. 0.5131 ** 0.4007 4.5668 0.0214

*Significance at 0.10 level



R-Squared suggests goodness of the fit which means how much of the dependant variables

movements can be explained by the independent variables in the study. Taking into consideration

table above we can see that R-Squares for the mean of all banks and Hong Leong Bank is quiet

similar, 0.515 and 0.513 or approximately 51.5% which means that 51.5% of the bank’s

profitability (ROAs) can be attributed or explained by the variables specifically real GDP growth

rate, inflation (consumer price index), and interest rate. When it comes to Public Bank, nearly 60%

of ROA can be explained by the explanatory variable. Lastly, the highest R-Square has Maybank,

0.8165, which indicates, that in the case of this bank, 81.65% of bank profitability can be explained

by the model, which includes real GDP growth rate, interest rate, and consumer price index or

inflation as the independent (explanatory) variables.

Adjusted R-Square just gives us the corrected R-Square when there are many equations but in

this paper there is only one equation hence the use of adjusted R-Square is irrelevant. In presented

regression there are F-statistics of 4.6183 and 4.566 for the mean of all banks and Hong Leong

Bank respectively, and P-values of 0.0207 and 0.0214 correspondingly, which means that with

95% confidence level can be assumed the above statement to hold true for the mean of all banks

and Hong Leong Bank. In other hand, the F-statistics for the Public Bank and Maybank are 6.335

and 19.287 respectively, with P-values of 0.0069 and 0.0000 correspondingly, which means with

99% confidence level we can believe that for Public Bank and Maybank the above statement to

hold true.

Individual Coefficients/Interpretations

Coefficients (Probabilities)

C RGDP CPI RINT

All Banks

(Mean)

0.4935**

(0.0454)

0.0583***

(0.0033)

0.0468

(0.3748)

0.0085

(0.6356)

Maybank

0.8581***

(0.0002)

0.0711***

(0.0001)

-0.011

(0.776)

-0.0293**

(0.0436)

Public

Bank

1.5219***

(0.0000)

0.055**

(0.0101)

-0.1239*

(0.0506)

-0.0027

(0.8912)

Hong

Leong

1.1864***

(0.0001)

0.03165*

(0.0562)

-0.1074**

(0.0413)

-0.0107

(0.5235)


50

Significance at 0.10 level



Based on table presented above for mean of all banks the equation will be:

ROAt = 0.4935 + 0.0583RGDPt + 0.0468CPIt + 0.0085RINTt + εt; where RGDP is significant

at 1% (p<α; 0.0033<0.01), while CPI and RINT are not significant. Real GDP growth rate “RGDP”

has the expected positive relationship with the bank profitability (ROA). More precisely, as the real

GDP rises by 1% there will be an increase in the all bank profitability (ROA) by 0.05%, and the

study assumes this relationship with 99% confidence level as the p value is 0.0033. Even though

economic theory suggests that there should be relationship between ROA and inflation (CPI) as

well real interest rates, like for instance in the case of individual banks which will be apparent later

in paper, for model comprising mean of all banks study found that they are statistically

insignificant although they have expected signs.

Alternatively, For the Maybnak the equation states that :

ROAt = 0.8581 + 0.0783RGDPt - 0.011CPIt - 0.0293RINTt + εt; where RGDP is significant at

1% (p<α; 0.0001<0.01), RINT is significant at 5% (p<α; 0.0436<0.05), while CPI is not

significant. Similar to the case of all banks, as the real GDP rises by 1% there will be an increase in

the Maybank profitability (ROA) by 0.07%, and we can assume this relationship with 99%

confidence level as the p value is 0.0000. However, in case of Maybank, real interest rate is also

significant, with negative relationship. More precisely the model forecasts that any increase in real

interest rates will contribute to a decrease in Maybank profitability, as the coefficient has a negative

sign on it -0.0293 and is significant at the 0.05 level. For Maybank too, inflation is not significant.

As for the Public Bank the equation shows that:

ROAt = 1.5219 + 0.055RGDPt – 0.1239CPIt - 0.0027RINTt + εt; where RGDP is significant

at 5% (p<α; 0.0101<0.05), CIP is significant as well at 5% (p<α; 0.0436<0.05), while RINT is not

significant. Likewise in previous two modules, as the real GDP rises by 1% there will be an

increase in the Public Bank profitability (ROA) by 0.05%, and study can assume this relationship

with 95% confidence level as the p value is 0.0101. However, in case of Public Bank, inflation is

significant, with negative relationship to profitability. More expressly the model forecasts that an

increase in CPI by 1% will contribute to a decrease in Public Bank profitability by 0.1239, as the

coefficient has a negative sign on it -0.1239 and is significant at the 0.05 level. Interestingly, real

interest rate is not significant variable for Public Bank. Lastly, for Hong Leong Bank, the

individual coefficient interpretation is similar like in case of Public Bank. The equation ROAt =

1.1864 + 0.03165RGDPt – 0.1074CPIt – 0.0107RINTt + εt shows that RGDP is significant at 10%

(p<α; 0.0562<0.01), significance of CPI is 5% (p<α; 0.0413<0.05), while RINT is not significant.

Likewise in previous modules, as the real GDP rises by 1% there will be an increase in the Public

Bank profitability (ROA) by 0.03%, and we can assume this relationship with 90% confidence

level as the p value is 0.0562. As in the case of Public Bank, inflation is significant, with negative


51

relationship to profitability. More specifically the model forecasts that an increase in CPI by 1%

will contribute to a decrease in Hong Leong Bank profitability by 0.1074, as the coefficient has a

negative sign on it -0.1239 and is significant at the 0.05 level. Real interest rate, as in the case of

the mean of all banks and Public Bank, is not significant variable for Hong Leong Bank.

7. CONCLUSION

This paper examines the relationship and dynamic linkage between profitability of Malaysian

commercial banks, expressed through return on assets (ROA) and macroeconomic variables which

comprise real GDP growth, inflation (expressed through CPI) and real interest rates. The analysis

relies on standard and well accepted techniques of linear regression and correlation utilizing the

data that span of 17 years or 17 annual observations.

7.1. Main Findings

The profitability of all banks together as well as three individual banks, Maybank, Public Bank

and Hong Leong Bank in Malaysia is investigated in this paper. The paper shows that the mean for

all banks, as well as three individual banks, real GDP is significant and have positive relationship

with banks’ profitability. This is consistent with majority of previous finding including Molyneux

and Thornton (1992) as well as Pasiouras and Kosmidou (2007). The paper, in accordance with

economic theory, explains that economic growth increases bank profits through enhanced demand

for business loans. These loans generate good returns to commercial banks, resulting in higher

profits.

Even though economic theory suggests that there should be relationship between ROA and

inflation (CPI), this paper presents that in Malaysian case for the mean of all banks and Maybank

inflation (CPI) is not significant. This result is consistent with findings of Naceur (2003) who

suggested that banks tend not to earn profit in inflationary environment. On the contrary, for Public

Bank and Hong Leong Bank inflation (CPI) is significant, showing a negative relationship. This

result is consistent with findings of Demirgüç-Kunt and Huizinga (1999) who advocated that in

case of unanticipated inflation banks may be slow in adjusting their interest rates, which will have

for outcome that bank costs increase faster than bank revenues, therefore negatively impact bank

profitability. Lastly, paper illustrated that in Malaysia real interest rate has no relation with banks’

profitability. For mean of all banks, Public Bank and Hong Leong Bank real interest rate (RINT) is

not significant. This result can be associated with study done by Guru et al. (1999) which suggested

that interest rate spread or margin should be used as explanatory variable in place of just real

market interest rates.

7.2. Implications

The findings of this paper indicate some implications pertaining to Malaysian banks’

profitability. Firstly, growth in GDP increases the banks’ profitability in Malaysia. The higher the

growth of GDP, the better is the Malaysian banks’ profitability. When there is a consistent growth


52

in GDP for a particular period of time, the business units would respond to the demand of goods

and services in the economy. The more efficient the funds or capitals would be matched by the

banking sector, the more it would spur economic activities and in turn further increase the demand

of funds and capitals to cater for the business activities in the economy. These increase business

activities would contribute to the GDP growth and hence the rapid economic development would

have positive impact on the banks’ profitability via advanced financial intermediation. Thus, it is

suggested that for the banks’ profitability, the growth of gross domestic product must be in place in

order to stimulate lending and borrowing activities. Secondly, inflation, if it is significant, seems to

have negative impact on some Malaysia’s banks. For instance, Public Bank and Hong Leong Bank

appear to be slow in adjusting their interest rates, therefore experiencing that bank costs increase

faster than bank revenues. Consequently this has a negative impact on banks’ profitability.

Accordingly, it is suggested that for the banking sector to preserve on profitability, the anticipation

of inflation must be in place in order to increase revenue and reduce cost.

7.3. Caveats

There is some gap in studying the profitability determinants of commercial banks in Malaysia

for the period 1995-2011. This paper tries to shed light on this gap. To begin with, there is a need

for more comprehensive study which covers all banks in Malaysia and for longer period. Study

should also include other factors which are not covered in this paper such as market concentration,

money supply and exchange rates. In addition, pre and after 1997 Financial Crisis comparison

research in the profitability determinants for Malaysian banks would be appropriate. Lastly, this

paper basically focused on the domestic commercial banks. Future researches may extend analysis

to include subsidiaries of foreign banks operating in Malaysia in their samples. To this extent, a

comparative analysis of the profitability performance of foreign and domestic banks could be

carried out.

REFERENCES

Aburime, T.U., 2008. Determinants of bank profitability: Industry-level evidence from

Nigeria. International Journal of Nigerian Studies and Development, 14: 21-34.

Alexiou, C. and V. Sofoklis, 2009. Determinants of bank profitability. Evidence from the

Greek Banking Sector. Economic Annals, 54(182):93-118.

Athanasoglou, P.P., S.N. Brissimis and M.D. Delis, 2008. Bank specific, industry specific

and macroeconomic determinants of bank profitability. Journal of International

Financial Markets, Institutions and Money, 18(2): 121–136.

Bourke, P., 1989. Concentration and other determinants of bank profitability in europe,

north america and australia. Journal of Banking & Finance, 13(1): 65-79.

Chantapong, S., 2005. Comparative study of domestic and foreign bank performance in

thailand. The Regression Analysis. Economic Change and Restructuring, 38(1):

63–83.


53

Chaudhry, M., A. Chatrath and K. R., 1995. Determinants of bank profitability American

Journal of Business, 10(1): 41-46.

Demirgüç-Kunt, A. and H. Huizinga, 1999. Determinants of commercial bank interest

margins and profitability. Some International Evidence. World Bank Economic

Review, 13(2): 379-408.

Goddard, J., P. Molyneux and J.O.S. Wilson, 2004. The profitability of european banks. A

Cross-Sectional and Dynamic Panel Analysis. The Manchester School, 72(3):

363-381.

Guru, B.K., J. Staunton and Balashanmugam, 1999. Determinants of commercial bank

profitability in Malaysia.

Kosmidou, K., 2008. The determinants of banks’ profits in greece during the period of eu

financial integration. Managerial Finance, 34(3): 146–159.

Kosmidou, K., F. Pasiouras and A. Tsaklanganos, 2007. Domestic and multinational

determinants of foreign bank profits: The case of greek banks operating abroad.

Journal of Multinational Financial Management, 17(1): 1-15.

Kosmidou, K., S. Tanna and F. Pasiouras, 2008. Determinants of profitability of domestic

uk commercial banks: Panel evidence from the period 1995–2002. Economics,

finance and accounting applied research working paper series, coventry university

business school.

Kosmidou, K. and C. Zopounidis, 2008. Measurement of bank performance in Greece.

South Eastern Europe Journal of Economics, 6(1): 79–95.

Mohd, S.R. and M.H. Tumin, 2011. Performance and financial ratios of commercial banks

in Malaysia and China. International Review of Business Research Papers, 7(2):

157-169.

Molyneux, P. and J. Thornton, 1992. Determinants of european bank profitability: A note.

Journal of Banking and Finance, 16(6): 1173-1178.

Naceur, S., 2003. The determinants of the tunisian banking industry profitability: Panel

evidence. ERF Research Fellow, Department of Finance, Université Libre de

Tunis.

Pasiouras, F. and K. Kosmidou, 2007. Factors influencing the profitability of domestic

and foreign commercial banks in the European Union. Research in International

Business and Finance, 21(2): 222-237.

Ramadan, I.Z., Q.A. Kilani and T.A. Kaddumi, 2011. Determinants of bank profitability:

Evidence from Jordan. International Journal of Academic Research, 3(4):180-191.

Rasiah, D., 2010. Theoretical framework of profitability as applied to commercial banks

in Malaysia. European Journal of Economics, Finance and Administrative

Sciences, 19: 74-97.

Saunders, A. and L. Schumacher, 2000. The determinants of bank interest rate margins:

An international study. Journal of International Money and Finance, 16(6): 813-

832.


54

Staikouras, C.K. and W.E. Geoffrey, 2004. The determinants of european bank

profitability. International Business & Economics Research Journal, 3(6):57-68.

Sufian, F., 2009. Determinants of bank efficiency during unstable macroeconomic

environment: Empirical evidence from Malaysia. Research in International

Business and Finance, 23(1): 54-77.

Sufian, F. and R.R. Chong, 2008. Determinants of bank profitability in a developing

economy: Empirical evidence from the philippines. Asian Academy of

Management Journal of Accounting and Finance 4(2): 91-112.

Sufian, F. and M.S. Habibullah, 2009. Bank specific and macroeconomic determinants of

bank profitability: Empirical evidence from the china banking sector. Frontiers of

Economics in China, 4(2): 274-294.

Sufian, F. and M.S. Habibullah, 2009. Determinants of bank profitability in a developing

economy: Empirical evidence from Bangladesh. Journal of Business Economics

and Management, 10(3): 207-217.

Sufian, F. and M.S. Habibullah, 2010. Does economic freedom fosters banks’

performance? Panel evidence from Malaysia. Journal of Contemporary

Accounting & Economics, 6(2): 77-91.

Tan, Y. and C. Floros, 2012. Bank profitability and inflation: The case of China. Journal

of Economic Studies, 39(6): 675-696.

Williams, B., 2003. Domestic and international determinants of bank profits: Foreign

banks in Australia. Journal of Banking and Finance, 27(6): 1185-1210.

Yu, H. and P.T. Gan, 2010. The determinants of banking sector development: Malaysian

experience. International Research Journal of Finance and Economics (35).

APPENDICES

Appendix-A. Jarque-Bera test

A1- All banks

A3 – Public Bank

0

1

2

3

4

5

6

-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5

Series: Residuals

Sample 1995 2011

Observations 17

Mean 7.94e-10

Median 0.006137

Maximum 0.452622

Minimum -0.570699

Std. Dev. 0.230934

Skewness -0.531373

Kurtosis 3.739915

Jarque-Bera 1.187805

Probability 0.5521680

1

2

3

4

5

6

7

8

-0.75 -0.50 -0.25 0.00 0.25 0.50 0.75

Series: ResidualsSample 1995 2011Observations 17

Mean -3.27e-09Median -0.009457Maximum 0.519657Minimum -0.545674Std. Dev. 0.260636Skewness 0.021718Kurtosis 2.927377

Jarque-Bera 0.005072Probability 0.997467


55

A2- Maybank

A4- Hong Leon Bank

Appendix-B. Breusch – Godfrey Serial Correlation LM Test

B1 – All Banks

Breusch-Godfrey Serial Correlation LM

Test:

F-statistic 1.353393 Prob. F(2,11) 0.2982

Obs*R-

squared 3.357123

Prob. Chi-

Square(2) 0.1866

B3 – Public Bank


Test:


Obs*R-

squared 1.696194

Prob. Chi-

Square(2) 0.4282

B2 – Maybank


Test:


Obs*R-

squared 5.814478

Prob. Chi-

Square(2) 0.0546

B4 – Hong Leong Bank


Test:


Obs*R-

squared 0.454322

Prob. Chi-

Square(2) 0.7968

Appendix C: Heteroskedasticity Test: White

C1 – All Banks

Heteroskedasticity Test: White


Obs*R-squared 10.18159 Prob. Chi-Square(3) 0.0171

Scaled explained SS 8.156643 Prob. Chi-Square(3) 0.0429

C3- Public Bank





0

1

2

3

4

5

6

-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3


Mean 3.53e-11Median -0.019557Maximum 0.209576Minimum -0.392986Std. Dev. 0.172410Skewness -0.460910Kurtosis 2.515718


0

1

2

3

4

5

6

7

-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3


Mean -2.61e-09Median 0.051905Maximum 0.264348Minimum -0.494506Std. Dev. 0.214953Skewness -1.008334Kurtosis 3.252703



56

C2- Maybank





C4- Hong Leong Bank





Appendix D: Ramsey’s Mis-specification test – RESET

D1 – All Banks

Ramsey RESET Test

Equation: EQ01

Specification: ROA C RGDP CPI RINT

Omitted Variables: Powers of fitted values from 2

to 3

Value df Probability

F-statistic 0.366519 (2, 11) 0.7013

Likelihood ratio 1.096726 2 0.5779

D3 – Public Bank

Ramsey RESET Test

Equation: EQ011



to 3


F-statistic 2.832744 (2, 11) 0.1018


D2 – Maybank

Ramsey RESET Test

Equation: EQ01



to 3


F-statistic 9.321107 (2, 11) 0.0043


D4 – Hong Leong Bank

Ramsey RESET Test

Equation: EQ01



to 3


F-statistic 1.659217 (2, 11) 0.2345


Appendix E: ARCH Test

E1 – All banks

Heteroskedasticity Test: ARCH


Obs*R-

squared 0.178953

Prob. Chi-

Square(1) 0.6723

E3- Public Bank



Obs*R-

squared 0.102829

Prob. Chi-

Square(1) 0.7485

E2 – Maybank



Obs*R-

squared 0.057116

Prob. Chi-

Square(1) 0.8111

E4-Hong Leong Bank



Obs*R-

squared 0.163272

Prob. Chi-

Square(1) 0.6862


57

Appendix-F. CUSUM and CUSUMSQ Test

F1 – All banks

F 2- Maybank

F3- Public Bank

F4- Hong Leong Bank

-12

-8

-4

0

4

8

12

99 00 01 02 03 04 05 06 07 08 09 10 11

CUSUM 5% Significance

-0.4

0.0

0.4

0.8

1.2

1.6

99 00 01 02 03 04 05 06 07 08 09 10 11

CUSUM of Squares 5% Significance

-12

-8

-4

0

4

8

12

99 00 01 02 03 04 05 06 07 08 09 10 11


-0.4

0.0

0.4

0.8

1.2

1.6

99 00 01 02 03 04 05 06 07 08 09 10 11


-12

-8

-4

0

4

8

12

99 00 01 02 03 04 05 06 07 08 09 10 11


-0.4

0.0

0.4

0.8

1.2

1.6

99 00 01 02 03 04 05 06 07 08 09 10 11


-12

-8

-4

0

4

8

12

99 00 01 02 03 04 05 06 07 08 09 10 11


-0.4

0.0

0.4

0.8

1.2

1.6

99 00 01 02 03 04 05 06 07 08 09 10 11


AN ANALYSIS OF MACROECONOMIC DETERMINANTS … 4(1), 41-57.pdf · AN ANALYSIS OF MACROECONOMIC...

Documents

Transcript of AN ANALYSIS OF MACROECONOMIC DETERMINANTS … 4(1), 41-57.pdf · AN ANALYSIS OF MACROECONOMIC...